Wiener Filter Image Restoration Based on MATLAB GUI
Image blurring is an important problem in digital image processing. In actual scenes, we often encounter various types of blur, such as motion blur, Gaussian blur, discrete Fourier transform blur, and so on. Blurring will affect the image quality, causing the loss of image detail information, loss of clarity, reduction of contrast, and so on. In order to solve these problems, we can use image restoration algorithms, and one of the common algorithms is to use Wiener filtering for image restoration.
Wiener filtering is an image restoration method based on the frequency domain, which is essentially a convolution and deconvolution process. By analyzing the frequency characteristics of the image, the image is filtered in the frequency domain to filter out unnecessary noise and blur, thereby realizing image restoration. This article will introduce in detail how to realize the restoration of images by Wiener filtering based on MATLAB GUI.
- Preparation
First, we need to prepare a blurred source image and a PSF (Point Spread Function) to blur the image. In MATLAB, the PSF of motion blur can be generated by the following code:
len = 21;
theta = 11;
PSF = fspecial('motion'